Field
Embodiments of the present invention generally relate to a system and method to provide customer service and particularly to a system and method for improving call routing process by utilizing resource selection strategies.
Description of Related Art
Contact centers are employed by many enterprises to service, inbound and outbound contacts or customers. A primary objective of contact center management is to ultimately maximize contact center performance and profitability. An ongoing challenge in contact center administration is monitoring and optimizing contact center efficiency usage of its available resources. The contact center efficiency is generally measured by metrics such as Service Level Agreement (SLA), Customer Satisfaction (CSAT), and match rate. Contact center resources may include, agents, communication assets (e.g., number of voice trunks, number and bandwidth of video trunks, etc.), computing resources (e.g., a speed, a queue length, a storage space, etc.), and so forth.
Service level is one measurement of the contact center efficiency. Service level is typically determined by dividing the number of contacts accepted within a specified period by the number accepted plus number that were not accepted, but completed in some other way (e.g., abandoned, given busy, canceled, flowed out). Service level definitions may vary from one enterprise to another.
Match rate is another indicator used in measuring the contact center efficiency. Match rate is usually determined by dividing the number of contacts accepted by a primary skill level agent within a period of time by the number of contacts accepted by any agent in a queue over the same period. An agent with a primary skill level is one who typically may handle contacts of a certain nature more effectively and/or efficiently as compared to an agent of lesser skill level. There are other contact center agents who may not be as proficient as the primary skill level agent, and those agents are identified either as skill level agents or backup skill level agents.
As can be appreciated, contacts received by a primary skill level agent are typically handled more quickly and accurately or effectively (e.g., higher revenue attained) than a contact received by a secondary or even backup skill level agent. Thus, it is an objective of most contact centers to optimize match rate along with the service level.
In addition to service level and match rate performance measures, contact centers use other Key Performance Indicators (“KPIs”), such as revenue, estimated, actual, or predicted wait time, average speed of answer, throughput, agent utilization, agent performance, agent responsiveness and the like, to calculate performance relative to their Service Level Agreements (“SLAs”). Operational efficiency is achieved when the KPIs are managed near, but not above, SLA threshold levels.
Throughput is a measure of the number of contacts/contact requests or work requests that may be processed in a given amount of time. Agent utilization is a measure of how efficiently the agents' time is being used. Customer service level is a measure of the time customers spend waiting for their work to be handled. Company contact center customers wish to provide service to as many requests as possible in a given amount of time, using the least number of agents to do so, and minimizing the wait time for their customers that may increase the Service Level Agreement (SLA) of the contact center. Further, the contact center may also have to maintain the Customer Satisfaction (CSAT) metrics in order to maintain the KPIs of the contact center. For this purpose, agents may have to maintain the quality of services provided to the customers through multimedia (e.g., voice contacts, video contacts, emails, etc.).
Generally, agents are selected based on routing strategies for providing customer services. These routing strategies are resource selection strategies that are generated within the contact center. The routing strategies can be considered as a prescribed process or a technique to find a most suitable resource for an incoming work request and/or how to match a resource to an incoming work request, and the like. These routing strategies are an integral part of the contact centers, which makes it difficult to add and/or modify these routing strategies. Therefore, it is hard to modify and/or generate new selection strategies within the contact center without a major update in conventional systems.
Conventionally, customers are generally flooded with options to select predefined routing strategies. The customers can select a predefined routing strategy from a list of available predefined routing strategies and then customer services are provided based on the selected strategies. However, in these techniques, the customers do not have an option to execute their own bespoke routing strategies within the contact center.
Further, as more and more customer requirements are solidifying and new strategies are being considered, variations of same predefined routing strategies are being statistically linked in a routing engine. This may result in increasing complexity and maintenance cost of the routing engine within the contact center. Also, if contact centers craft more selection strategies based on the needs of the customers, then this may further create a management and implementation burden on routing engines of the contact centers.
There is thus a need for a system and method for selecting agents to improve call routing by using resource selection strategies in an enterprise.